International Journal of Engineering and Advanced Technology Studies (IJEATS)

EA Journals

Autocorrelation Function

A Statistical Approach to Study Pitch Variation for Prediction of Voice Disorder (Published)

The human voice is a magical tool to communicate, express emotions, to create wonderful music through singing. Everyone has a distinct voice, different from all others; almost like a fingerprint, one’s voice is unique and can act as an identifier. Unfortunately we never give much attention to the voice problem that can limit our ability to communicate and to complete daily activities. Voice disorders have a higher rate of occurrence among those who are in professions that require speaking, like teachers, aerobatic instructors, lawyers, social workers etc. Symptoms of a voice disorder range from hoarseness or a chronic dry, scratchy throat, a pitch/tone that is not pleasing, limitations in the ability to speak clearly, or periods of voice loss. Voice disorder may be attributed to the abnormality in the structure and/or function of the larynx (vocal folds) as well as the abnormalities of its different components, making each voice different; namely, pitch, tone, and rate. In this paper a statistical approach is investigated on pitch quality to make early prediction of voice disorder for professional talkers.

Keywords: Autocorrelation Function, Electroglottography, Kymographic parameters, Phonation, Spectral density, Vocal folds

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